Design of Three-Dimensional Intelligent Guidance Law for Intercepting Highly Maneuvering Target

Abstract

This paper investigates the three-dimensional guidance and control problem of missile intercepting highly maneuvering target, whose acceleration information is difficult to accurately predict. With the three-dimensional guidance model for intercepting single target established by using the principle of zeroing the rate of line-of-sight (LOS), a novel intelligence guidance law has been designed through backstepping sliding mode control method, radial basis function (RBF) neural network and adaptive control technique. Then, a Lyapunov-based stability analysis demonstrates that all the signals are bounded, and the LOS rates ultimately converge to a neighborhood of the origin. Following advantages are highlighted in this paper: (i) the target information is online estimated and compensated by the RBF neural network, which indicates that the proposed guidance law is easily put into practice only relying on the position information of target. (ii) an adaptive gain term is designed in the control system, which greatly reduces the inherent chattering of sliding mode method. At last, simulations are conducted, and results illustrate the effectiveness and superiority of the designed guidance law.INDEX TERMS Missile intercepting, guidance law, backstepping sliding mode control, RBF neural network, adaptive control.

Design of Missile Guidance Law Using Takagi-Sugeno-Kang (TSK) Elliptic Type-2 Fuzzy Brain Imitated Neural Networks

“…Recently, neural networks (NNs) have been successfully applied in nonlinear system [6], especially for aerospace engineering [7], NN for steering law for manoeuvring targets [8], NN of missile guidance control [9]. Su et al presented a guidance law in [8], which was developed using the backstepping method of sliding mode control, a radial basis function (RBF) neural network, and an adaptive control technique. A Lyapunov-based stability analysis shows that all signals are bounded and the LOS rates eventually converge near the origin.…”